\(\color{darkblue}{\textbf{Spatial Data}}\)

---

\(\color{dodgerblue}{\textbf{Components}}\)

Spatial Data = Coordinates + Coordinate Reference System (CRS)

A common CRS is latitude/longitude

• Latitude = position North to South
• Longitude = position East to West

Type	Latitude	Longitude
Standard	44.57808N	123.2803W
Coding	44.57808	-123.2803
	+N, -S	+E, -W

Often it is written as: (longitude, latitude)

Thus: (-123.2803, 44.57808)

---

\(\color{dodgerblue}{\textbf{Types}}\)

\(\color{darkblue}{\textbf{Spatial R}}\)

---

library(sf)

\(\color{dodgerblue}{\textbf{Reading in Data}}\)

spatial <- read_sf("pathway/to/shapefile.shp")

spatial <- read_csv("pathway/to/spatial.csv") %>% 
  st_as_sf()

---

\(\color{dodgerblue}{\textbf{Setting CRS}}\)

Name	Code
World Geodetic System 1984 (WGS 84)	4326
NAD83 / New York Long Island	2263

spatial <- read_sf("pathway/to/shapefile.shp") %>% 
  st_transform(2263)

---

\(\color{dodgerblue}{\textbf{Removing Geometry}}\)

non_spatial <- spatial %>% 
  st_set_geometry(NULL)

---

\(\color{dodgerblue}{\textbf{Plotting}}\)

#ny_counties <- read_sf(dataset with county shapefiles)

borough_halls <- tibble(lon = c(-73.990540,
                                -73.923790,
                                -73.921090,
                                -74.075960,
                                -74.003740),
                        lat = c(40.692631,
                                40.826270,
                                40.743600,
                                40.642400,
                                40.713010),
                        boro = c("Brooklyn",
                                 "Bronx",
                                 "Queens",
                                 "Staten Island",
                                 "Brooklyn")) 

borough_halls_geo <- borough_halls %>% 
  st_as_sf(coords = c("lon", "lat"), 
           crs = 2263)


ggplot() + 
  geom_sf(data = ny_counties) + 
  geom_sf(data = borough_halls_geo) + 
  theme(axis.text.x = element_blank(),
        axis.text.y = element_blank(),
        axis.ticks = element_blank(),
        rect = element_blank())

\(\color{darkblue}{\textbf{New York City}}\)

---

\(\color{dodgerblue}{\textbf{City}}\)

---

\(\color{dodgerblue}{\textbf{Borough/County}}\)

---

\(\color{dodgerblue}{\textbf{Community District}}\)

• Created by the City through local law in 1975 to serve as political units

---

\(\color{dodgerblue}{\textbf{Sub-Borough Area/PUMA}}\)

• The Census’ approximation of Community Districts
• Statistical areas defined for Public Use Microdata Sample (PUMS)

---

\(\color{dodgerblue}{\textbf{Neighborhood Tabulation Area}}\)

• Created by the City to project populations at a small area level (min 15,000 people) for PlaNYC
• Based on Census Tracts (meaning they line up with PUMAs and not Community Districts)

---

\(\color{dodgerblue}{\textbf{ZIP Codes}}\)

• Created by USPS for the purposes of sorting and delivering mail
• Not related to neighborhoods, political districts, or demographics
• Not coterminous with census tracts, CDs, SBAs, or even boroughs
• Approximated by the Census as ZCTAs

---

\(\color{dodgerblue}{\textbf{Borough, Block, and Lot (BBL)}}\)

• Created by the Department of Finance for taxes, zoning, construction, and other purposes
• Ideally one building sits on a single lot that has one owner who pays taxes on the building
• Search by property or BBL here

---

\(\color{dodgerblue}{\textbf{Building Identification Number (BIN)}}\)

• Created by the Department of Buildings to uniquely identify every individual building
• Process = Building permit filed with DOB > DOB creates temporary BIN (TBIN) > DOB issues a Certificate of Occupancy > DOB adds BIN to address database (PAD) > DoITT adds building footprint

---

\(\color{dodgerblue}{\textbf{PLUTO}}\)

• Comprehensive land use dataset and key here